Economic Threshold for Dynamically Optimal Late Blight Management

This study evaluates economic thresholds for a new web-based decision support system developed for precision fungicide management for potato production. We extend previous work (Zhang and Swinton, 2009), by developing an intra-seasonal dynamic economic optimization model. This model allows us to evaluate economic thresholds for disease control. The suggested model is applied to the problem of controlling potato late blight disease in 152 locations for 5 major potato producing states in the United States. The empirical results show that the economic thresholds improved disease suppression and farming profit relative to the previous critical thresholds while maintaining fungicide use efficiency.

[1]  D. Shtienberg,et al.  Development and evaluation of a general model for yield loss assessment in potatoes. , 1990 .

[2]  William E. Fry,et al.  Development and implementation of the BlightPro decision support system for potato and tomato late blight management , 2015, Comput. Electron. Agric..

[3]  H. Platt,et al.  Diseases, Pests and Disorders of Potatoes: A Colour Handbook , 2006 .

[4]  J. Guenthner,et al.  The economic impact of potato late blight on US growers , 2001, Potato Research.

[5]  W. Fry,et al.  Evaluation of the BlightPro Decision Support System for Management of Potato Late Blight Using Computer Simulation and Field Validation. , 2015, Phytopathology.

[6]  P. Hamm,et al.  Potato Late Blight in the Columbia Basin: An Economic Analysis of the 1995 Epidemic. , 1997, Plant disease.

[7]  R. A. Krause.  Blitecast; a computerized forecast of potato late blight. implementation and evaluation , 1976 .

[8]  Wei Zhang,et al.  Incorporating natural enemies in an economic threshold for dynamically optimal pest management. , 2009 .

[9]  Robert Faivre,et al.  Modeling of Yield Losses Caused by Potato Late Blight on Eight Cultivars with Different Levels of Resistance to Phytophthora infestans. , 2012, Plant disease.

[10]  D. Inglis,et al.  Testing for resistance to metalaxyl inPhytophthora infestans isolates from northwestern Washington , 1993, American Potato Journal.

[11]  C. Mundt,et al.  Retardation of potato late blight epidemics by fungicides with eradicant and protectant properties. , 1979 .

[12]  J. Goldstrom,et al.  'The visitation of god?' The potato and the great Irish famine. , 1994 .

[13]  D. Shtienberg,et al.  Simulation of Potato Late Blight in the Andes. II: Validation of the LATEBLIGHT Model. , 2005, Phytopathology.

[14]  M. Langemeier,et al.  Risk management strategies using potato precision farming technology , 2015 .

[15]  William E. Fry,et al.  Evaluation of potato late blight forecasts modified to incorporate host resistance and fungicide weathering , 1983 .

[16]  R. Young,et al.  Occurrence of the A2 mating type ofPhytophthora infestans in potato fields in the United States and Canada , 1991, American Potato Journal.

[17]  S. B. Goodwin,et al.  Re-emergence of Potato and Tomato Late Blight in the United States. , 1997, Plant disease.

[18]  J. R. Wallin,et al.  Summary of recent progress in predicting late blight epidemics in United States and Canada , 1962, American Potato Journal.

[19]  W. Fry,et al.  Computer simulation raises question about timing protectant fungicide application frequency according to a potato late blight forecast , 1984 .

[20]  G. Starr,et al.  Microclimate and potential for late blight development in irrigated potato , 2007 .

[21]  R. Hijmans,et al.  Simulation of Potato Late Blight in the Andes. I: Modification and Parameterization of the LATEBLIGHT Model. , 2005, Phytopathology.

[22]  S. B. Goodwin,et al.  Widespread distribution and probable origin of resistance to metalaxyl in clonal genotypes of Phytophthora infestans in the United States and Western Canada , 1996 .

[23]  M. Powelson,et al.  Potato health management , 2008 .